Computational identification of natural product leads that inhibit mast cell chymase: an exclusive plausible treatment for Japanese encephalitis

Abstract

A recent research has identified chymase, a mast cell-specific protease as an exclusive novel therapeutic target to prevent Japanese encephalitis virus (JEV) induced encephalitis. Interestingly, JEV activates mast cell specific chymase during its penetration through blood brain barrier (BBB) which eventually guide to viral encephalitis. Hence, in this study, natural chemical entities (NCE) from multiple databases (MPD3, TIPDB and MTDP) were virtually screened for their binding affinity as chymase inhibitors, a promising negotiator for prolong survival against JEV tempted encephalitis. Merged computational programs, Maestro software, QikProp, ProTox and Gromacs were applied to screen the NCEs against target receptor (PDB: 4KP0). Three hits (C00008437, C00014417 and 8141903) were identified after employing a series of sieves such as High Throughput Virtual Screening (HTVS), Standard precision (SP) and Xtra precision (XP) molecular docking simulations followed by desired pharmacokinetic-toxicity profile predictions and molecular dynamics (MD) examinations. Maestro simulations resulted in best three binding energy scores as −11.992 kcal/mol (first ranked; C00008437), −11.673 kcal/mol (second ranked; C00014417) and −11.456 kcal/mol (third ranked; 8141903), respectively. The top three hits revealed an ideal range of pharmacokinetic and toxicity descriptors values. In addition, MD simulations enabled us to confirm top hits higher selectivity toward chymase receptor. In conclusion, this might potentially represent remarkable novel classes with an effective chymase mediated treatment to combat JEV induced encephalitis, which need to justify with further detail studies.

Graphical Abstract

Communicated by Ramaswamy H. Sarma

Keywords:

• Japanese encephalitis virus
• chymase
• natural chemical entities
• molecular docking
• pharmacokinetic
• toxicity
• molecular dynamics

Acknowledgments

Dr. Kamal Kant and Dr. Subham Banerjee sincerely thanks to the Dr. U.S.N. Murty, Director, NIPER-Guwahati for his precious guidance. Dr. Anoop Kumar is grateful to Dr. S.J.S. Flora, Director, NIPER-Raebareli for his continues encouragement and required facility during this research work.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.